Study-Unit Description

Study-Unit Description


CODE LLT1002

 
TITLE Techniques and Skills for the Analysis of Language Data

 
UM LEVEL 01 - Year 1 in Modular Undergraduate Course

 
MQF LEVEL 5

 
ECTS CREDITS 4

 
DEPARTMENT Institute of Linguistics and Language Technology

 
DESCRIPTION This study-unit provides students with techniques and skills for working with linguistic data from a variety of languages. Practice in close-reading of specified texts will serve as an entry point into a review of key concepts necessary for uncovering and explaining patterns in linguistic data at different levels of structure. Students will be trained to look for these patterns, make observations and formulate generalisations by developing the appropriate metalanguage for this. Different ways of working with linguistic data will be explored and practised in the course of the study-unit, allowing students to improve step-by-step their observational and analytical skills. Whilst most of the data which will serve as the basis for analysis will be curated, tools for processing data in preparation for analysis, some of which will have been introduced in other study-units, will also be referenced.

Study-Unit Aims:

- Provide students with experience in the analysis and interpretation of linguistic datasets;
- Help students identify theoretically-relevant patterns in linguistic data and formulate generalisations on the basis of their observations;
- Give students the conceptual and technical grounding, as well as the metalanguage needed, to account for different types of phenomena found in different languages.

Learning Outcomes:

1. Knowledge & Understanding:

By the end of the study-unit the student will be able to:

- Define the importance of pattern recognition for linguistic data analysis;
- Recognise that linguistic data is characterised by patterns at different levels of structure;
- Observe and identify patterns based on a firm understanding of relevant concepts;
- Formulate generalisations based on these observations;
- Recognise the link between data and theory on the basis of practical application.

2. Skills:

By the end of the study-unit the student will be able to:

- Analyse linguistic data by applying relevant concepts and techniques to the analysis;
- Uncover patterns in such data using appropriate tools;
- Use different techniques and skills as a function of the data and the aims of the analysis;
- Formulate simple generalisations based on observation and analysis;
- Develop formal accounts with reference to relevant concepts.

Main Text/s and any supplementary readings:

Main Texts:

- Carnie, A. (2013). The syntax workbook: A companion to Carnie’s Syntax. Wiley-Blackwell.
- Coates, R. (1999). Word structure. [Language Workbooks series]. Routledge.
- Cowan, W., & Rakusan, J. (1999). Source book for linguists. 3rd ed. John Benjamins Publishing Company.
- Farmer. A. K. & Demers, R.A. (2001) A Linguistics Workbook. MIT Press.
- Roca, I., & Johnson, Wyn. (1999). A workbook in phonology. Blackwell Publishers.

 
ADDITIONAL NOTES Pre-requisite Study-units: LLT1011 and LLT1012 or Equivalent
Pre-requisite Qualification: LLT1011 and LLT1012 or Equivalent

 
STUDY-UNIT TYPE Lecture

 
METHOD OF ASSESSMENT
Assessment Component/s Assessment Due Sept. Asst Session Weighting
Analysis Task SEM2 30%
Examination (2 Hours) SEM2 70%

 
LECTURER/S Ray Fabri (Co-ord.)
Sarah Grech
Alexandra Vella

 

 
The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints.
Units not attracting a sufficient number of registrations may be withdrawn without notice.
It should be noted that all the information in the description above applies to study-units available during the academic year 2025/6. It may be subject to change in subsequent years.

https://www.um.edu.mt/course/studyunit